Title :
A novel method for linking reviews with database objects
Author :
Zhang Yong-Xin ; Li Qing-Zhong ; Sun Tao ; Xu Yuan-Zi
Author_Institution :
Sch. of Comput. Sci. & Technol., Shandong Univ., Jinan, China
Abstract :
In this paper, we proposed a method for linking reviews with database objects problem in data integration, where each object has a set of attributes. To this end, we propose a method based on 2-layer Conditional Random Fields (CRF). First, we show how to apply Semi-Markov CRF to effectively exploit a variety of entity-level features available in integrated data, thereby significantly reducing the dependence on manually labeled training data. Based on the identified entities of the first stage, we link entity reviews with database objects using CRF. Experiments in multiple domains show that our method can substantially superior to traditional tf-idf based methods as well as a recent language model-based method for the review matching problem.
Keywords :
Markov processes; database management systems; conditional random fields; data integration; database objects; linking reviews; review matching; semi-Markov CRF; Data mining; Data models; Databases; Dictionaries; Hidden Markov models; Motion pictures; Training; Semi-Markov CRF; review matching; web data integration;
Conference_Titel :
Mechatronic Science, Electric Engineering and Computer (MEC), 2011 International Conference on
Conference_Location :
Jilin
Print_ISBN :
978-1-61284-719-1
DOI :
10.1109/MEC.2011.6025885